Survey of automated multiple sclerosis lesion segmentation techniques on magnetic resonance imaging
A Danelakis, T Theoharis, DA Verganelakis - … Medical Imaging and …, 2018 - Elsevier
Multiple sclerosis (MS) is a chronic disease. It affects the central nervous system and its
clinical manifestation can variate. Magnetic Resonance Imaging (MRI) is often used to …
clinical manifestation can variate. Magnetic Resonance Imaging (MRI) is often used to …
Evaluating white matter lesion segmentations with refined Sørensen-Dice analysis
The Sørensen-Dice index (SDI) is a widely used measure for evaluating medical image
segmentation algorithms. It offers a standardized measure of segmentation accuracy which …
segmentation algorithms. It offers a standardized measure of segmentation accuracy which …
Compound attention embedded dual channel encoder-decoder for ms lesion segmentation from brain MRI
Multiple Sclerosis (MS) lesions' segmentation is difficult due to their variegated sizes,
shapes, and intensity levels. Besides this, the class imbalance problem and the availability …
shapes, and intensity levels. Besides this, the class imbalance problem and the availability …
LIFE: a generalizable autodidactic pipeline for 3D OCT-A vessel segmentation
Optical coherence tomography (OCT) is a non-invasive imaging technique widely used for
ophthalmology. It can be extended to OCT angiography (OCT-A), which reveals the retinal …
ophthalmology. It can be extended to OCT angiography (OCT-A), which reveals the retinal …
[HTML][HTML] Multiple sclerosis lesion detection in multimodal MRI using simple clustering-based segmentation and classification
Background Multiple sclerosis (MS) is an immune-mediated inflammatory disease that
attacks myelinated axons in the central nervous system, destroying myelin and axons to …
attacks myelinated axons in the central nervous system, destroying myelin and axons to …
Self-fusion for OCT noise reduction
Reducing speckle noise is an important task for improving visual and automated
assessment of retinal OCT images. Traditional image/signal processing methods only offer …
assessment of retinal OCT images. Traditional image/signal processing methods only offer …
Deep network and multi-atlas segmentation fusion for delineation of thigh muscle groups in three-dimensional water–fat separated MRI
NV Annasamudram, AM Okorie… - Journal of Medical …, 2024 - spiedigitallibrary.org
Purpose Segmentation is essential for tissue quantification and characterization in studies of
aging and age-related and metabolic diseases and the development of imaging biomarkers …
aging and age-related and metabolic diseases and the development of imaging biomarkers …
[HTML][HTML] Image harmonization improves consistency of intra-rater delineations of MS lesions in heterogeneous MRI
Clinical magnetic resonance images (MRIs) lack a standard intensity scale due to
differences in scanner hardware and the pulse sequences used to acquire the images …
differences in scanner hardware and the pulse sequences used to acquire the images …
Saliency based deep neural network for automatic detection of gadolinium-enhancing multiple sclerosis lesions in brain MRI
J Durso-Finley, DL Arnold, T Arbel - … Held in Conjunction with MICCAI 2019 …, 2020 - Springer
The appearance of contrast-enhanced pathologies (eg lesion, cancer) is an important
marker of disease activity, stage and treatment efficacy in clinical trials. The automatic …
marker of disease activity, stage and treatment efficacy in clinical trials. The automatic …
Mapping the Spatial Distribution of Lesions in Stroke: Effect of Diffeomorphic Registration Strategy in the ATLAS Dataset
BB Avants, NJ Tustison - Lesion-to-Symptom Mapping: Principles and …, 2022 - Springer
Large-scale neuroimaging datasets from chronic stroke patients offer the opportunity to
better understand patterns of injury, concomitant behavioral impairments, and long-term …
better understand patterns of injury, concomitant behavioral impairments, and long-term …